Senior Engineering Manager - Machine Learning

Super; Madrid; On-site; EUR 60,000 - 90,000; Full time

Job summary

Super is seeking a motivated Senior Engineering Manager for Applied Machine Learning & Research in Madrid. You will lead a team in developing machine-learning systems that enhance the online gambling and sports-betting experience, transforming data into actionable insights.

Your role combines technical contributions, project management, and team leadership, guiding data scientists and ML engineers to deliver high-quality solutions.

Super believes diverse perspectives drive better performance, so they nurture talent based on ability and potential.

Qualifications

• 4+ years of experience in machine-learning and data-science roles.
• 5+ years of experience in leading or managing engineering teams.
• Strong programming skills in Python and experience with deep-learning frameworks.

Responsibilities

• Design, develop, and deploy advanced machine-learning models.
• Manage and prioritize machine-learning projects.
• Lead and mentor a team of data scientists and ML engineers.

Skills

Machine learning expertise

Team leadership

Python programming

Cloud computing (AWS)

Communication skills

Education

Master’s or Ph.D. in Computer Science/Data Science/Machine Learning

Tools

TensorFlow

PyTorch

Docker

Kubernetes

Job description

About the Role

We’re looking for a hands‑on and motivated Senior Engineering Manager for Applied Machine Learning & Research to support the development and delivery of machine‑learning systems at Super Technologies. The team harnesses data to revolutionize the online gambling and sports‑betting experience, transforming complex data into actionable insights that enhance customer engagement, trust, and satisfaction. In this role you will split your time between technical contribution, project coordination, and people management – helping your team succeed while staying close to the code.

Qualifications

• Master’s or Ph.D. in Computer Science, Data Science, Machine Learning, or a related field
• Proven experience (4 + years) in machine‑learning and data‑science roles
• Proven experience (5 + years) in leading or managing engineering teams, supporting the growth and performance of engineers
• Strong programming skills in Python and experience with deep‑learning frameworks such as TensorFlow, PyTorch, or JAX
• Experience with cloud computing platforms primarily AWS and containerisation technologies (e.g., Docker, Kubernetes)
• Excellent problem‑solving skills and the ability to work independently and collaboratively
• Strong communication and interpersonal skills

Preferred Qualifications

• Experience in the gaming or entertainment industry
• Experience with tools and technologies such as Spark, Snowflake, Qwak, MLFlow, Airflow, etc.
• Contributions to open‑source AI/ML projects or participation in AI/ML competitions (e.g., Kaggle)
• Experience with training and fine‑tuning large‑scale foundation models (e.g., GPT, BERT, T5) for various tasks
• Publications in top AI conferences, such as AAAI, IJCAI, NeurIPS, ICML, ICLR

Responsibilities

• Technical Expertise
  • Design, develop, and deploy advanced machine‑learning models to solve complex business problems
  • Stay updated with the latest trends and advancements in machine‑learning and AI technologies
  • Conduct code reviews and ensure best practices in model development and deployment
• Project Management
  • Manage and prioritise machine‑learning projects to align with business goals and objectives
  • Ensure timely delivery of high‑quality machine‑learning solutions
  • Coordinate with cross‑functional teams to integrate machine‑learning models into production systems
• People Management
  • Lead and mentor a team of 4‑5 data scientists and ML engineers, providing guidance and support in their day‑to‑day activities
  • Oversee the execution, development, growth, and performance of the ML team
  • Foster a collaborative and innovative team environment while building strong partnerships with product management and stakeholders

Equal Opportunity & Diversity

We hire and grow talent based on ability and potential, regardless of background and identity because we believe diverse perspectives drive better performance.